Introduction: Streaming LLM responses transforms the user experience from waiting for complete responses to seeing text appear in real-time, dramatically improving perceived latency. Instead of staring at a loading spinner for 5-10 seconds, users see the first tokens within milliseconds and can start reading while generation continues. But implementing streaming properly involves more than just […]
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LLM Fallback Strategies: Building Reliable AI Applications (Part 2 of 2)
Introduction: LLM APIs fail. Rate limits hit, services go down, models return errors, and responses sometimes don’t meet quality thresholds. Building reliable AI applications requires robust fallback strategies that gracefully handle these failures without degrading user experience. A well-designed fallback system tries alternative models, implements retry logic with exponential backoff, caches successful responses, and provides […]
Read more →LLM Routing and Model Selection: Optimizing Cost and Quality in Production
Introduction: Not every query needs GPT-4. Routing simple questions to cheaper, faster models while reserving expensive models for complex tasks can cut costs by 70% or more without sacrificing quality. Smart LLM routing is the difference between a $10,000/month AI bill and a $3,000 one. This guide covers implementing intelligent model selection: classifying query complexity, […]
Read more →Semantic Caching for LLM Applications: Cut Costs and Latency by 50%
Introduction: LLM API calls are expensive and slow. A single GPT-4 request can cost cents and take seconds—multiply that by thousands of users asking similar questions, and costs spiral quickly. Semantic caching solves this by recognizing that “What’s the weather in NYC?” and “Tell me NYC weather” are essentially the same query. Instead of exact […]
Read more →Google Gemini API: Building Multimodal AI Applications with 2M Token Context
Introduction: Google’s Gemini API represents a significant leap in multimodal AI capabilities. Launched in December 2023, Gemini models are natively multimodal, trained from the ground up to understand and generate text, images, audio, and video. With context windows up to 2 million tokens and native Google Search grounding, Gemini offers unique capabilities for building sophisticated […]
Read more →Serverless AI Architecture: Building Scalable LLM Applications
Three years ago, I built my first serverless LLM application. It failed spectacularly. Cold starts made responses take 15 seconds. Timeouts killed long-running requests. Costs spiraled out of control. After architecting 30+ serverless AI systems, I’ve learned what works. Here’s the complete guide to building scalable serverless LLM applications. Figure 1: Serverless AI Architecture Overview […]
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